Marijke Van Moerbeke
A random effects model for the identification of differential splicing (REIDS) using exon and HTA arrays
Van Moerbeke, Marijke; Kasim, Adetayo; Talloen, Willem; Reumers, Joke; Göhlmann, Hinrick W.H.; Shkedy, Ziv
Authors
Adetayo Kasim
Willem Talloen
Joke Reumers
Hinrick W.H. Göhlmann
Ziv Shkedy
Abstract
Background: Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes. Unfortunately, aberrant splicing events do occur which have been linked to genetic disorders, such as several types of cancer and neurodegenerative diseases (Fan et al., Theor Biol Med Model 3:19, 2006). Therefore, understanding the mechanism of alternative splicing and identifying the difference in splicing events between diseased and healthy tissue is crucial in biomedical research with the potential of applications in personalized medicine as well as in drug development. Results: We propose a linear mixed model, Random Effects for the Identification of Differential Splicing (REIDS), for the identification of alternative splicing events. Based on a set of scores, an exon score and an array score, a decision regarding alternative splicing can be made. The model enables the ability to distinguish a differential expressed gene from a differential spliced exon. The proposed model was applied to three case studies concerning both exon and HTA arrays. Conclusion: The REIDS model provides a work flow for the identification of alternative splicing events relying on the established linear mixed model. The model can be applied to different types of arrays.
Citation
Van Moerbeke, M., Kasim, A., Talloen, W., Reumers, J., Göhlmann, H. W., & Shkedy, Z. (2017). A random effects model for the identification of differential splicing (REIDS) using exon and HTA arrays. BMC Bioinformatics, 18(1), Article 273. https://doi.org/10.1186/s12859-017-1687-8
Journal Article Type | Article |
---|---|
Acceptance Date | May 15, 2017 |
Online Publication Date | May 25, 2017 |
Publication Date | May 25, 2017 |
Deposit Date | Jun 20, 2017 |
Publicly Available Date | Jun 21, 2017 |
Journal | BMC Bioinformatics |
Publisher | BioMed Central |
Peer Reviewed | Peer Reviewed |
Volume | 18 |
Issue | 1 |
Article Number | 273 |
DOI | https://doi.org/10.1186/s12859-017-1687-8 |
Files
Published Journal Article
(2.2 Mb)
PDF
Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/
Copyright Statement
© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
You might also like
Multisite educational trials: estimating the effect size and its confidence intervals
(2021)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search